A National Consortium to Explore the Genotypic Basis for ESRD in Lupus (Robert P. Kimberly, MD (site PI); NIAMS RC2AR058951)
End stage renal disease (ESRD), one of the most serious and costly complications of systemic lupus erythematosus (SLE), occurs in a sub-set of patients with SLE-related renal involvement. Factors predisposing to ESRD presumably include both genetics and environmental factors, and there is unequivocal evidence that ESRD disproportionately affects lupus persons of African American descent. Data in SLE-related ESRD suggest that at least two genetic factors, -- certain allelic variants of the genes FCGR3A and MYH9, -- contribute to ESRD risk. However, two genes alone do not define the scope of genetic risk for ESRD. Therefore, building on our precedent data for genetic contributions, it is timely to undertake a genome-wide association study (GWAS) to identify the genetic risk factors for ESRD in European American (EA) and African Americans (AA) with lupus nephritis (LN/ESRD). Until now, two major barriers have precluded such a study. Technical limitations in genotyping platform and coverage have been overcome with the Illumina Human Omni- 1 Quad BeadChip. To surmount the second barrier of limited study populations, we have assembled an unprecedented team of rheumatologists, nephrologists and statistical geneticists with IRB protocols active, the clinical studies infrastructure in place and the patient collections and clinical data more than 75% in hand. Thus (1) Our first aim is to characterize the genetic susceptibility factors associated with ESRD by performing a GWAS with 800 EA LN/ESRD and 800 AA LN/ESRD compared to lupus subjects of each ethnicity but without nephritis and normal control subjects. (2) We propose that [gene x gene] and [gene x environment] interactions are biologically important and may be more easily detectable using the machine learning and more modern likelihood-based approaches. Therefore, our second aim is to apply novel approaches to gene discovery and biological pathway characterization including Bayesian networks, alternative decision trees, HyperLasso, and penalized logistic regression. (3) Finally, our third aim is to build an essential resource, consistent with NIH specimen and data sharing guidelines and supported by the institution. This resource will enable follow-up studies in fine-mapping, deep-sequencing, SNP identification, pathway analysis and methods development. Our consortium leverages current resources and investments by NIAMS, NIDDK, NIEHS, NCRR, CDCP and private foundations to create a unique opportunity to address a major health care challenge. We have a substantial head start, drawing on established networks and clinical research infrastructure, and are poised to identify genetic risk factors, leading to strategies for ESRD reduction, which would enable substantial cost savings and reduction in morbidity and mortality as it reduces ethnic disparities in health outcomes.